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Claudio Luchinat CERM Università di Firenze Centro Europeo di Risonanze Magnetiche una infrastruttura di ricerca nel Polo Scientifico dellUniversità di.

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Presentation on theme: "Claudio Luchinat CERM Università di Firenze Centro Europeo di Risonanze Magnetiche una infrastruttura di ricerca nel Polo Scientifico dellUniversità di."— Presentation transcript:

1 Claudio Luchinat CERM Università di Firenze Centro Europeo di Risonanze Magnetiche una infrastruttura di ricerca nel Polo Scientifico dellUniversità di Firenze

2 Il Polo Scientifico di Sesto Fiorentino

3 800 700b 850ss 700 400 500 Bio-labs Library 700s s 900 GENEXPRESS, CRYST, CISM Department of Chemistry (offices, bio-labs, relaxometer, instruments..) Workshop Conference room 600b The Magnetic Resonance Center in Florence Computer room 600 DaVEB Biobank 950

4 NMR instrumentation CERM instrumentation 400 MHz 600 MHz Cryo 700 MHz (a) Cryo 700 MHz (b) Cryo 500 MHz Cryo 900 MHz Cryo 800 MHz 700 MHz WB 850 MHz WB Cryo 600 MHz Cryo 950 MHz

5 800 700b 850ss 700 400 500 Bio-labs Library 700s s 900 GENEXPRESS, CRYST, CISM Department of Chemistry (offices, bio-labs, relaxometer, instruments..) Workshop Conference room 600b The Magnetic Resonance Center in Florence Computer room Electron/nuclear relaxation (Relaxometry) Drug discovery Structural proteomics Metabolomics Protein structure determination Methodological advancements in NMR Solid state NMR ICT and computational biology 600 DaVEB Biobank We provide access to European researchers since 1994 New access program Bio-NMR (2010-2014) started September 2010 Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, Goteborg 950

6 Claudio Luchinat CERM Università di Firenze Metabolomica: uno sguardo molecolare sulla salute e sulle malattie

7 The Research Centers of FiorGen CERM Scientific Campus Sesto Fiorentino Biomedical Campus Careggi

8 Scientific Publications 146 publications on high level journals, starting from 2004 Independent reviewers attested the high scientific level of the Foundation The scientific production of FiorGen is quite impressive Prof. Arturo Falaschi Scuola Normale Superiore – Pisa Distinguished Scientist ICGEB Trieste Aprile 2008 The scientific productivity of FiorGen is of excellent level Prof. Giuseppe Novelli Tor Vergata University of Rome University of Arkansas (USA) WPQ PGx EMEA (UK) Maggio 2008

9 What is Metabolomics? Metabolomics is a further omic science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites in an organism or cell. Genomics tells you what could happen. Metabolomics tells you what has happened. Only a few thousand metabolites. !! However, not negligible external variability !! (source of noise)

10 Acetyl CoA Examples of metabolites O O OH Pyruvic acid O OH O HO Succinic acid O O HO O OH Oxaloacetic acid

11 Study of small molecules in biological fluids +Metabolomics Metabolic fingerprint

12 1 H NMR spectrum of ethanol CC H H H H H H O __ | | | |

13 1H NMR spectrum (upfield part) of human urine

14 1H NMR spectrum (downfield part) of human urine

15 1234567ppm Quantitative methods Chemometric methods (fingerprinting and pattern recognition) Two approaches: Identify as many metabolites as possible Identify as many metabolites as possible Use the whole spectrum as a fingerprint (statistics) Use the whole spectrum as a fingerprint (statistics) 2 Routes to Metabolomics

16 The fingerprint Few already known metabolites for some disease (e.g. glucose for diabetes, etc…) Metabolomics : Traditional clinical analysis: All metabolites are analyzed together without prior knowledge

17 The fingerprint What are they doing ?

18 The fingerprint Only an analysis at a global level can tell the whole story

19 Ind 1 Ind 2 METabolomic REFerence

20 Ind 1 Ind 2 METabolomic REFerence

21 Convex hulls of 22 donors in the three most significant PCA-CA dimensions Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008, 105, 1420-4 PCA for data reduction CA for obtain well separated clusters KNN for classification 99% accuracy in montecarlo cross validation natural gender discrimination MALEFEMALE

22 Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009 There exists an individual human metabolic phenotype (metabotype) The metabotype consists of a variable part (environment) and an invariant part (genetics + environment) The invariant part persists for at least two-three years (if the diet is averaged using collection of multiple samples) The discovery of the existence of individual metabotypes is the baseline for Biomedical Researches Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008 The signature of Our Body

23 Metabolomics @CERM/CIRMMP Collaborative Projects SPIDIA (7th framework program) Standardization and improvement of pre-analytical procedures for in-vitro diagnostics. CHANCE (7th framework program) Evaluation of the impact of nutritional criticalities in population at risk of poverty using NMR metabolomics. livSYSiPS (ErasysBio+)livSYSiPS (ErasysBio+) The sistem biology of network stress based on data generated from in vitro differentiated hepatocytes derived from individual-specific human iPS cells. ITFoM (FET Flagship Initiative) The aim of ITFoM is to develop models of human pathways, tissues, and ultimately of the whole human, to create a virtual patient which will enable physicians to identify personalised prevention schedules and treatments adapted to each person. Progetto COSMOS (EU Coordination action) To develop new standard for metabolomics sutdies Progetto BioMedBridges (EU Coordination action) To develop a unified framework for biomedical studies in Europe Progetto Melanoma (Ente Cassa di Risparmio di Firenze) New strategies for diagnosis prognosis and treatment of melanoma.

24 Metabolomics @CERM/CIRMMP Collaborations Celiac Disease (Prof. Antonio Calabrò, Careggi Hospital) Geriatric patients (Dr. Laura Biganzoli, Prato Hospital) Diabetes in young (Dr. Sonia Toni, Mayer Childrens Hospital) BPCO (Dr. Massimo Miniati, Careggi Hospital and CNR Pisa) Metastatic Colorectal Cancer (Dr. Benny W. Jensen, Herlev Hospital, Copenhagen) Periodonitis (Dr. Mario Aimetti, University of Turin) Bladder and Prostate Cancer (Dr. Marco Carini, Careggi Hospital) Cardiovascular Risk (Dr. Adriana Tognaccini, Pistoia Hospital and AVIS Toscana) Intestinal Bowel Diseases (Prof. Maurizio Vecchi, University of Milan) Heart Failure (Prof. Franco Gensini, University of Florence) Breast Cancer (Dr. Angelo Di Leo, Prato Hospital) Bariatric Surgery (Prof. Bernd Schultes, St. Gallen Hospital, Switzerland) Metabolomics of the Mitochondrion (Prof. Roland Lill, University of Marburg, Germany) Osteoarthritis (Prof. Brandi, University of Florence) Krabbe disease (Dott.sa Alice Luddi, University of Siena) Gestational diabetes (Dr. Dani, Careggi Hospital)

25 Celiac Disease Metabolomics Clusterization of Celiac and Healthy subject serum spectra Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

26 Celiac Disease Metabolomics Clusterization of Celiac and Healthy subject serum spectra and corresponding Follow-up Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

27 Celiac disease Celiac – Healthy Subjects – Cross: predicted Potential Celiac Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J. Proteome Res. 2010 There exist a metabolic fingerprint of celiac disease These alteration are present also in potential celiac subjects: so they precede the intestinal damage Potential CD largely shares the metabonomic signature of overt CD. Most metabolites found to be significantly different between control and CD subjects were also altered in potential CD. Our results suggest early institution of GFD in patients with potential CD Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

28 http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

29 Breast cancer metabolomics Healthy vs Met Accuracy 73.44% Healthy vs Post-op Accuracy 75.80% Post vs Met Accuracy 74.96% NOESY Healthy vs Met Accuracy 72.67% Healthy vs Post-op Accuracy 70.00% Post-op vs Met Accuracy 70.00% CPMG Classification between Pre-Op and Metastatic subjects. Accuracy ~80% Other comparisons

30 Colorectal Cancer Metabolomics Cross-validated results on the Training Set: Sensitivity :79.9% Specificity:76.4% Accuracy:78.5% Univariate Cox Regression Analysis for the Validation Set: HR:3.30 95% CI:2.02 to 5.37 P:1.75 10 -6 PLS-CA model: long survival, in blue; short survival, in yellow Serum samples from 139 HS and 155 patients with mCRC, included in a prospective phase II study of 3rd line treatment with cetuximab and irinotecan We can discriminate healthy controls from mCRC with almost 100% accuracy. We can predict the overall survival of the patients Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P., Cancer Res. 2012 Jan 1;72(1):356-64. Epub 2011 Nov 11

31 SensitivitySpecificityAccuracy CMD vs CMS 45.52%68.29%61.19% NYHA1 vs NYHA 2 61.88%71.42%67.71% NYHA2 vs NYHA 3/4 73.62%56.44%68.04% NYHA 1 vs NYHA 3/4 74.83%68.55%72.15% Classification between different subgroups of Heart failure patients (1D CPMG spectra). Patients are separated from healthy, but there is not any significant difference between the disease grading that could reflect the clinical severity of the disease. Although good discrimination between healthy and HF subjects with a severe disease, if not expected, was easy to be hypothesized, a comparable good discrimination ability between healthy and HF subjects with a mild disease was unexpected and appears rather counter-intuitive. Heart failure metabolomics Patients vs Healthy85.11%91.04%87.29%

32 Metabolomics of Melanoma NOESY SpectraSERUMURINE Sensitivity (%)Specificity (%)Accuracy (%) Sensitivity (%) Specificity (%)Accuracy (%) Healthy vs. Melanoma91.3881.6789.8995.4670.5291.37 Stage I/II vs. Healthy85.4985.3485.2591.0379.0287.46 Stage III/IV vs. Healthy88.8491.4089.385.4480.2582.93 Stage I/II vs III/IV85.1873.2879.9475.4067.8672.98

33 Fingerprint of Obesity Fingerprint of obesity NW vs SO 94.0 OW vs SO 79.6 NW vs OW 69.7 NW vs OW+SO 87.8 NW+OW vs SO 84.1 The prediction of OW (stars) using the NW (green) vs SO (blue) model classify almost all OW as SO (except two)

34 Da Vinci European BioBank

35 Metabolomica Lapproccio combinato di metabolomica (Prof. Claudio Luchinat) e biobanca (Prof. Paola Turano) ci rende unici in questo settore della scienza Spettro NMR di urina di un donatore sano FROM METABOLOMICS Metabolomic analysis Validation of sample quality in biobanks Definition of new SOPs TO BIOBANKS Dalla Metabolomica Analisi Metabolomica Controllo Qualità di campioni Nelle biobanche Definizione di Nuove SOP Alle Biobanche http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

36 Fiorgen ha implementato una Biobanca su standard europei che è inserita nei programmi nazionali ed europei. Essa raccoglie campioni biologici (sangue, urine, biopsie) di molte malattie. Collezioni di campioni della Biobanca: 1. Scompenso cardiaco (Prof. Gianfranco Gensini) 2. Melanoma (Prof. Nicola Pimpinelli) 3. Cancro alla mammella (Prof. Angelo Di Leo, e USA) 4. Cancro al colon (Prof. Benny V. Jensen, Danimarca) 5. Disturbi alla prostata (Prof. Marco Carini) 6. Celiachia (Prof. Antonio Calabrò) 7. Osteoporosi (Prof.ssa Maria Luisa Brandi) http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

37 The Future of Medicine Metabolomics can monitor the same individual in a multidimensional space Intestinal bowel disease Hypertension hepatocarcinoma steatosis cirrhosis Diabetes Metabolic syndrome Colorectal cancer Hearth Failure Healthy aging

38 Et interviene di questa come dicono e fisici dello etico, che nel principio del suo male è facile a curare e difficile a conoscere, ma, nel progresso del tempo, non lavendo in principio conosciuta né medicata, diventa facile a conoscere e difficile a curare. Machiavelli, Il Principe, cap. 3

39 Il sogno Dotare ogni cittadino di un chip in cui sono riportati il genoma, il proteoma e il metaboloma al fine di monitorarne nel tempo lo stato di salute http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

40 The Future of Medicine From general to personalized medicine

41 Ivano Bertini December 6, 1940 – July 7, 2012

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44 Metabolomics @CERM/CIRMMP Metabolomics Publications Human phenotypes Assfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M. Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci U S A 2008;105(5):1420-4. (IF=9.771). Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L. Individual human phenotypes in metabolic space and time. J Proteome Res. 2009 Sep;8(9):4264-71. (IF=5.460). Cardiovascular diseases Bernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples. J Proteome Res 2011. [Epub ahead of print] (IF=5.460). Celiac disease Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011 Feb 4;10(2):714-21. (IF=5.460). Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L. The metabonomic signature of celiac disease. J Proteome Res. 2009 Jan;8(1):170-7. (IF=5.460). Ozono terapy Travagli V, Zanardi I, Bernini P, Nepi S, Tenori L, Bocci V. Effects of ozone blood treatment on the metabolite profile of human blood. Int J Toxicol 2010;29(2):165-74. (IF=1.762).

45 Metabolomics @CERM/CIRMMP Breast cancer Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC, Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: A pilot study. Mol Oncol. 2012 Jun 1. (IF=4.250). Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E, Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Ann Oncol 2011 Jun;22(6):1295-301. (IF=6.452). Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011 Jul;43(7):1010-20. Review. (IF=4.956). Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: available results, current research projects in breast cancer, and future applications. J Clin Oncol. 2007 Jul 1;25(19):2840-6. (IF=18.970). Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol. 2007;18 Suppl 12:xii8-14. Review. (IF=6.452). Colorectal Cancer Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res. 2012 Jan 1;72(1):356-64. (IF=8.234).

46 Metabolomics @CERM/CIRMMP Peridontal diseases Mario Aimetti, Stefano Cacciatore, Antonio Graziano and Leonardo Tenori. Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics; Online First (IF=3.608). Standard Operating Procedures Bernini P, Bertini I, Luchinat C, Nincheri P, Staderini S, Turano P. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR. 2011 Apr;49(3-4):231-43. (IF=3.047). The future of medicine Bertini I; Luchinat C; Tenori L. Metabolomics for the future of personalized medicine through information and communication technologies. PERSONALIZED MEDICINE Volume: 9 Issue: 2 (IF=0.783).

47 Metabolic signature of individuals: Metabolic phenotype Metabolic signature of diseases Coeliac disease tumor metastasis heart failure, pulmonary diseases,etc… Metabolites and biobank samples Sensitive reporters of stability Assess sample preparation and preanalytical procedures SOP Our interest in metabolomics

48 NMR analysis Metabolites identification Data processing and bucketing Statistical analysis Handling and preparation of samples Metabolomics steps

49 Collect Store Processing Distribute Biological samples for scientific research BioBank Project

50 The Future of Medicine The need for individual metabolomic screening We are proposing to collect individual metabolomics data for a large screening of the Tuscany population

51 The FiorGen Foundation

52 FiorGen Foundation, a non-profit organization of social utility (ONLUS), was founded in 2002, with the purpose of favoring scientific, cultural and social development. FiorGen Foundation is the result of a strong link between different scientific actors such as the Magnetic Resonance Center (CERM) of the Scientific Campus of Sesto Fiorentino and the Biomedical Campus of Careggi, which has been supported by the Chamber of Commerce, Industry and Handicrafts of Florence and the Ente Cassa di Risparmio of Florence. How was FiorGen born

53 ADMINISTRATION COUNCIL Vasco Galgani (President) Calogero Surrenti (Vicepresident) Gianni Amunni Paolo Asso Lucia Banci Francesco Barbolla Ivano Bertini Gianfranco Gensini Claudio Luchinat SCIENTIFIC COMMITTEE Ivano Bertini (President) Rosanna Abbate Andrea Galli Maurizio Genuardi Cristina Nativi Governing Bodies

54 Charity auction Art and Solidarity for the research Campaign "Adopt a Researcher" Fund Raising CF: 94100210486

55 n. 1 n.2 n.3 n.4Communication Newsletter FiorGenews

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61 Research Area 1: Bersagli e farmaci antitumorali Agonisti di recettori nucleari nella modulazione della crescita ed invasività tumorale Delezione organo specifica del recettore ARP-1 in modelli murini Research Area 2: Fisiopatologia e farmacogenetica delle malattie cardiovascolari Progetto Malattia Aneurismatica e Carotidea Progetto variabilità nella risposta alla terapia antiaggregante (aspirina e clopidogrel) Research Area 3: Origine malattie genetiche Studio delle basi genetiche della predisposizione a neoplasie umane Studi sull'origine della Sclerosi Laterale Amiotrofica Caratterizzazione strutturale della proteina beta amiloide coinvolta nel morbo di Alzheimer Research Area 4: Metabolomica Research Area 5: BioBanca da Vinci European BioBank - daVEB Research Area 6: Melanoma: nuovi possibili biomarcatori di diagnosi e progressione Research Areas of FiorGen


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